SUO: Re: Inquiry Driven Systems
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Inquiring Minds,
Correcting a few typos and continuing on:
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[ Document History:
| Project: Intelligent Dynamic Systems Engineering
| Heading: Original Interest Statement
| Authors: Jon Awbrey
| Version: Draft 5
| Created: 1991-Nov-12
| Revised: 1992-Sep-01
| Revised: 2001-Jan-04
| Setting: Oakland University, Rochester, Michigan
| Excerpt: Pages 1-3
]
Intelligent Dynamic Systems Engineering: Original Interest Statement
September 1, 1992
Jon Awbrey
It seemed useful, as a way of sharpening my focus on goals ahead,
to write up an extended statement of current research interests
and directions. I realize that many features of this sketch are
likely to change as details are clarified and as new experience
is gained. As an alternative to the longer essay, an abstract
is provided as a minimal statement.
Abstract
In briefest terms my project is to develop mutual applications
of systems theory and artificial intelligence to each other.
In the current phase of investigation I am taking a standpoint
in systems theory, working to extend its concepts and methods
to cover increasingly interesting classes of intelligent systems.
A natural side-project is directed toward improving the economy
of effort by unifying a selection of tools being used in these
two fields. My instrumental focus is placed on integrating the
methods of differential geometry with the techniques of logic
programming. I will attempt to embody this project in the form
of computer-implemented connections between geometric dynamics
and logical AI, and I will measure its success by the extent
and usefulness of this realization.
Description of Current & Proposed Work
I intend to focus primarily on the research area of
artificial intelligence. In my work of the past few
years I have sought to apply the framework of systems
theory to the problems of AI. I believe that viewing
intelligent systems as dynamic systems can provide
a unifying perspective for the array of problems and
methods that currently constitutes the field of AI.
The return benefits to systems theory would be equally
valuable, enabling the implementation of more intelligent
software for the study of complex systems. The engineering
of this software could extend work already begun in simulation
modeling (Widman, Loparo, & Nielsen, 1989), (Yip, 1991), nonlinear
dynamics and chaos (Rietman, 1989), (Tufillaro, Abbott, & Reilly, 1992),
and expert systems (Bratko, Mozetic, & Lavrac, 1989), with increasing
capabilities for qualitative inference about complex systems and for
intelligent navigation of dynamic manifolds (Weld & de Kleer, 1990).
1. Background
In my aim to connect the enterprises of systems theory
and artificial intelligence I recognize the following facts.
Although the control systems approach was a prevailing one
in the early years of cybernetics and important tributaries
of AI have sprung from its sources, e.g. (Ashby, 1956), (Arbib,
1964, '72, '87, '89), (Albus, 1981), the two disciplines have
been pursuing their separate evolutions for many years now.
The intended scope of AI, overly ambitious or otherwise, forced it
to break free of early bonds, shifting for itself beyond the orbit
of its initial paradigms and the cases that conditioned its origin.
A sample of materials from transition phases of AI's developmental
crises may be found in (Shannon & McCarthy, 1956), (Wiener, 1961, 1964),
(Sayre & Crosson, 1963), (Young, 1964, 1978), (McCulloch, 1965), (Cherry, 1966),
(MacKay, 1969). Any project to resolder the spun-off domains of AI and systems
theory will probably resort to a similar flux. In the course of this investigation
it was surprising at first to see these old issues rise again, but the shock has
turned to recognition. A motion to reinstate thought with action, to amalgamate
intelligence with dynamics in computational simulation, will naturally revert to
the neighborhoods of former insights and ride the transits of formative ideas.
It is only to be expected that this essay will run across many of the most
intersected rights-of-way, if not traveling down and tripping over the very
same ruts, then very likely switching onto a number of parallel tracks.
Informed observers may see good reasons for maintaining the separation
of perspectives between AI and systems theory. However, the proposition
that these two realms share a common fund of theory and practice, not only
historically but one that demands and deserves a future development, is an
assertion that motivates my efforts here. Consequently, I thought that
a justification of my objectives might be warranted. In light of these
facts I have written up this extended rationale and informal review of
literature, in hopes of making a plausible case for attempting this work.
Rudiments & Horizons
There are harvests of complexity which sprout from the earliest elements
and the simplest levels of the discussion that follows. I will try to
clarify a few of these issues in the process of fixing terminology.
This may create an impression of making much ado about nothing, but
it is a good idea in computational modeling to forge connections
between the complex, the subtle, and the simple -- even to the
point of forcing things a bit. Further, I will use this space
to profile the character and the consistency of the grounds
being tended by systems theory and AI. Finally, I will let
myself be free to mention features of this work that connect
with the broader horizons of human cultivation. Although these
concerns are properly outside the range of my next few steps,
I believe that it is important to be aware of our bearings:
to know what our practice depends upon, to think what our
activity impacts upon.
1.1 Topos: Rudiments & Immediate Resources
This inquiry is guided by two questions that express themselves in
many different guises. In their most laconic and provocative style,
self-referent but not purely so, they typically bring a person to ask:
| Why am I asking this question?
| How will I answer this question?
Cast in with a pool of other questions these two often act as efficient
catalysts of the inquiry process, precipitating and organizing what results.
Expanded into general terms these queries become tantamount to asking:
| What accumulated funds and immediate series of experiences lead up
| to the moment of surprise that causes the asking of a question?
| What operational resources and planned sequences of actions lead on
| to the moment of solution that allows the ending of a problem?
Phrased in systematic terms, they ask yet again:
| What capacity enables a system to exist in states of question?
| What competence enables a system to exit from its problem states?
1.1.1 Systematic Inquiry
In their underlying form and tone these questions sound a familiar tune.
Their basic tenor was brought to a pitch of perfection by Immanuel Kant,
in a canon of inquiry that exceeds my present range. Luckily, my immediate
aim is much more limited and concrete. For the present it is only required
to ask: "How are systematic inquiry and knowledge possible?" That is, how
are inquiry and knowledge to be understood and implemented as functions of
systems and how ought they be investigated by systems theory? In short:
"How can systems have knowledge as a goal?" This effort is constrained
to the subject of systems and the frame of systems theory. It will attempt
to give system-theoretic analyses of concepts and capacities that can be
recognized as primitive archetypes, at least, of the those that AI research
pursues with avid interest and aspires one day to more more fully capture.
By limiting questions about the possibility of inquiry and knowledge to the
subject and scope of systems theory there may be reason to hope for a measure
of practical success.
Kant's challenge is this: To say precisely 'how' it is possible,
in procedural terms, for contingent beings and empirical creatures,
physically embodied and even engineered systems, to move toward or
synthetically acquire forms of knowledge with an 'a priori' character,
that is, declarative statements with a global application to all of the
situations that these agents might pass through. It is not feasible within
the scope of systems theory and engineered systems to deal with the larger
question: Whether these forms of knowledge are somehow 'necessary' laws,
applying to all conceivable systems and universes. But it does seem
reasonable to ask how a system's trajectory might intersect with states
whose associated knowledge components have a wider application to the
system's manifold as a whole.
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To Be Continued ...
Jon Awbrey
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